Nuclear Magnetic Resonance Diffusion Research Articles

Intact NMR Approach Quickly Reveals Synchronized Microstructural Changes in Oil-in-Water Nanoemulsion Formulations

A soft-core oil-in-water (o/w) nanoemulsion (NE) is composed of nanometer (nm) sized oil droplets, stabilized by a surfactant layer and dispersed in a continuous bulky water phase. Characterization of the o/w NE molecule arrangements non-invasively, particularly the drug phase distribution (DPD) and its correlation to oil globule size (OGS), remains a challenge. Here we demonstrated the analytical methods of intact 19F Nuclear Magnetic Resonance (NMR) and 1H diffusion ordered spectroscopy (DOSY) NMR for their specificity in measuring DPD and OGS, respectively, on three NE formulations containing the active ingredient difluprednate (DFPN) at the same concentration. The results illustrated synchronized molecular rearrangement reflected in the DPD and OGS upon alterations in formulation. Addition of surfactant resulted in a higher DPD in the surfactant layer, and concomitantly smaller OGS. Mechanic perturbation converted most of the NE globules to the smaller thermodynamically stable microemulsion (ME) globules, changing both DPD and OGS to ME phase. These microstructure changes were not observed using 1D 1H NMR; and dynamic light scattering (DLS) was only sensitive to OGS of ME globule in mechanically perturbed formulation. Collectively, the study illustrated the specificity and essential role of intact NMR methods in measuring the critical microstructure attributes of soft-core NE systems quickly, accurately, and non-invasively. Therefore, the selected NMR approach can be a unique diagnostic tool of molecular microstructure or Q3 property in o/w NE formulation development, and quality assurance after manufacture process or excipient component changes.Graphical abstract

Diffusion Nuclear Magnetic Resonance Measurements on Cationic Gold (I) Complexes in Catalytic Conditions: Counterion and Solvent Effects.

The amount of free ions, ion pairs, and higher aggregate of the possible species present in a solution during the gold(I)-catalyzed alkoxylation of unsaturated hydrocarbon, i.e., ISIP (inner sphere ion pair) [(NHC)AuX] and OSIP (outer sphere ion pairs) [(NHC)Au(TME)X] [NHC 1,3-bis(2,6-di-isopropylphenyl)-imidazol-2-ylidene; TME = tetramethylethylene (2,3-bis methyl-butene); X- = Cl-, BF4-, OTf-; and OTs- BArF4- (ArF = 3,5-(CF3)2C6H3)], has been determined. The 1H and 19F DOSY NMR measurements conducted in catalytic conditions indicate that the dissociation degree (α) of the equilibrium ion pair/free ions {[(NHC)Au(TME)X] [(NHC)Au(TME)]+ + X-} depends on the nature of the counterion (X-) when chloroform is the catalytic solvent: while the compounds containing OTs- and OTf- as the counterion gave a low α (which means a high number of ion pairs) of 0.13 and 0.24, respectively, the compounds containing BF4- and BArF4- showed higher α values of 0.36 and 0.32, respectively. These results experimentally confirm previous deductions based on catalytic and theoretical data: the lower the α value, the greater the catalytic activity because the anion that can activate methanol during a nucleophilic attack, although the lower propensity to activate methanol of BF4- and BArF4-, as suggested by the DFT calculations, cannot be completely overlooked. As for the effect of the solvent, α increases as the dielectric constant increases, as expected, and in particular, green solvents with high dielectric constants show a very high α (0.90, 0.84, 0.80, and 0.70 for propylene carbonate, γ-valerolactone, acetone, and methanol, respectively), thus confirming that the moderately high activity of NHC-Au-OTf in these solvents is due to the specific effect of polar functionalities (O-H, C=O, O-R) in activating methanol. Finally, the DOSY measurements conducted in p-Cymene show the formation of quadrupole species: under these conditions, the anion can better exercise its 'template' and 'activating' roles, giving the highest TOF.

Exploring the Potential of Machine Learning Algorithms to Improve Diffusion Nuclear Magnetic Resonance Imaging Models Analysis

Purpose: This paper explores different machine learning (ML) algorithms for analyzing diffusion nuclear magnetic resonance imaging (dMRI) models when analytical fitting shows restrictions. It reviews various ML techniques for dMRI analysis and evaluates their performance on different b-values range datasets, comparing them with analytical methods. Materials and Methods: After standard fitting for reference, four sets of diffusion-weighted nuclear magnetic resonance images were used to train/test various ML algorithms for prediction of diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and kurtosis (K). ML classification algorithms, including extra-tree classifier (ETC), logistic regression, C-support vector, extra-gradient boost, and multilayer perceptron (MLP), were used to determine the existence of diffusion parameters (D, D*, f, and K) within single voxels. Regression algorithms, including linear regression, polynomial regression, ridge, lasso, random forest (RF), elastic-net, and support-vector machines, were used to estimate the value of the diffusion parameters. Performance was evaluated using accuracy (ACC), area under the curve (AUC) tests, and cross-validation root mean square error (RMSECV). Computational timing was also assessed. Results: ETC and MLP were the best classifiers, with 94.1% and 91.7%, respectively, for the ACC test and 98.7% and 96.3% for the AUC test. For parameter estimation, RF algorithm yielded the most accurate results The RMSECV percentages were: 8.39% for D, 3.57% for D*, 4.52% for f, and 3.53% for K. After the training phase, the ML methods demonstrated a substantial decrease in computational time, being approximately 232 times faster than the conventional methods. Conclusions: The findings suggest that ML algorithms can enhance the efficiency of dMRI model analysis and offer new perspectives on the microstructural and functional organization of biological tissues. This paper also discusses the limitations and future directions of ML-based dMRI analysis.

NMR diffusion in restricted environment approached by a fractional Langevin model

The diffusion motion of spin-bearing molecules is considerably affected in confined environments. In Nuclear Magnetic Resonance (NMR) experiments, under the presence of magnetic field gradients, this movement can be encoded in spin phase and the NMR signal attenuation due to diffusion can be evaluated. This paper considered this effect in both normal and anomalous diffusion by means of the Langevin stochastic model within the Gaussian phase approximation (GPA) for a constant gradient temporal profile. The phenomenological approach illustrates the emergence of fractional order exponential decay in the NMR signal and retrieves the classical result from Hanh echo.

Structure and activity of amphiphilic PEO-PPO-based polymeric micelles and gels incorporating host–guest complexes of miltefosine as novel formulations for the treatment of leishmaniasis

Hypothesis: Poloxamines are amphiphilic block copolymers that self-assemble forming polymeric micelles (PMs) and hydrogels. They have emerged as promising colloidal carriers for their potential in improving drug delivery and controlled release through their multi-responsive properties. Tetronic® 1307 (T1307) PMs and gels have been used herein as vehicles of host–guest complexes of cyclodextrins (CDs) and miltefosine (MF), an amphiphilic, anti-parasitic drug effective against leishmaniasis.Experiments: The association of MF to αCD, βCD, and HPβCD and the topology of the complexes have been fully characterized by NMR spectroscopy. Then, the structure of the complex-loaded PMs and hydrogels investigated using diffusion nuclear magnetic resonance (DOSY), small angle neutron scattering (SANS), and dynamic light scattering (DLS). The antileishmanial activity of the constructs was evaluated against Leishmania major promastigotes and amastigotes, as well as their cytotoxicity in macrophages.Findings: All the CDs investigated form highly stable inclusion complexes with MF in a 2CD:1MF stoichiometry that lead to considerable proportions of complexed drug at high dilution, the HPβCD providing the highest stability and compatibility with the poloxamine. The complex incorporates preferentially into the hydrophilic shell of the PMs, inducing the elongation of the aggregates and the dehydration of the micellar core, formed mainly by the PPO blocks. At high concentration of polymer and physiological temperature, the complex-loaded PMs pack in a BCC-type paracrystal network. The micellar formulations of the CD-complexed MF reduced the cytotoxicity of the drug, while enhancing its antileishmanial activity. This approach could improve the currently available treatments, facilitating the administration of MF at lower concentrations and achieving relevant therapeutic effects, not only through the intravenous route, but also as topical formulations through injectable thermogels for the treatment of the cutaneous and mucocutaneous forms of the disease.

Quantitative at-line monitoring of enzymatic hydrolysis using benchtop diffusion nuclear magnetic resonance spectroscopy.

Benchtop diffusion nuclear magnetic resonance (NMR) spectroscopy was used to perform quantitative monitoring of enzymatic hydrolysis. The study aimed to test the feasibility of the technology to characterize enzymatic hydrolysis processes in real time. Diffusion ordered spectroscopy (DOSY) was used to measure the signal intensity and apparent self-diffusion constant of solubilized protein in hydrolysate. The NMR technique was tested on an enzymatic hydrolysis reaction of red cod, a lean white fish, by the endopeptidase alcalase at 50°C. Hydrolysate samples were manually transferred from the reaction vessel to the NMR equipment. Measurement time was approximately 3 min per time point. The signal intensity from the DOSY experiment was used to measure protein concentration and the apparent self-diffusion constant was converted into an average molecular weight and an estimated degree of hydrolysis. These values were plotted as a function of time and both the rate of solubilization and the rate of protein breakdown could be calculated. In addition to being rapid and noninvasive, DOSY using benchtop NMR spectroscopy has an advantage compared with other enzymatic hydrolysis characterization methods as it gives a direct measure of average protein size; many functional properties of proteins are strongly influenced by protein size. Therefore, a method to give protein concentration and average size in real time will allow operators to more tightly control production from enzymatic hydrolysis. Although only one type of material was tested, it is anticipated that the method should be applicable to a broad variety of enzymatic hydrolysis feedstocks.

Catalytic Cracking of 1,3,5‐Triisopropylbenzene and Low‐Density Polyethylene over Hierarchical Y Zeolites and Al‐SBA‐15

AbstractCatalytic cracking of high molecular weight hydrocarbons underpins the production of fossil fuels from petroleum vapour and the recycling of polyolefin waste plastic. However, thermal cracking over conventional microporous solid acids is hindered by poor mass‐transport. Here we explore the performance of hierarchical H−Y zeolites and Al‐SBA‐15 for the catalytic cracking of 1,3,5‐triisopropylbenzene (1,3,5‐TIPB) and low‐density polyethylene (LDPE) in a continuous fixed‐bed flow reactor. Dealumination by acid washing was used to create hierarchical mesoporosity in H−Y zeolite and modify the solid acidity. Physicochemical properties were studied by X‐ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), gas adsorption, in‐situ Fourier transform infrared (FTIR), ex‐situ pyridine DRIFT, 29Si and 27Al nuclear magnetic resonance (NMR), and 1H relaxation and pulsed field gradient (PFG) NMR diffusion studies. Despite weakening acidity, the introduction of hierarchical porosity promotes deep cracking of both feedstocks; HNO3 dealuminated H−Y produces five times more cumene and benzene from 1,3‐5‐TIPB, and 33 % more benzene and xylenes from LDPE, than the parent H−Y.

Towards All-Extruded Custom-Shape Batteries

The rapid growth of flexible electronics for wearable devices, on-skin or environmental sensors, and flexible displays have resulted in intensive research in the field of free form-factor energy-storage systems. Since batteries must withstand bending, folding, or stretching while maintaining their electrochemical performance, the design and processing of battery components, must be reconsidered. Moreover, there is a clear tendency to shift battery technology to clean and cost-effective dry methods with no toxic solvents. Dry fabrication methods are environmentally friendly, involve lower energy consumption, shorter time and are cost-effective. Hot-pressing and melting-extrusion strategies are appropriate for the fabrication of flexible, solid-polymer electrolytes and electrodes with high contents of active materials and high mass loading.Here we present the progress towards the simple, one-step extrusion of a solid-state battery with a multi-shell and layered architecture. Such structures fundamentally minimize the ionic pathway for Li+. As in the conventional battery, high ionic conductivity of extruded electrolyte and compatibility with electrode materials, are the essential properties for enabling high performance of the battery. The electrolytes are composed of LiTFSI, polyethylene oxide (PEO), which is a known lithium-ion conductor, and thermoplastic recyclable and biodegradable polymer- polyurethane (TPU) - for enhanced mechanical properties and high-temperature durability. The extruded electrolytes of different PEO-to-TPU ratios and salt content were characterized by means of ESEM imaging, mass spectroscopy, differential-scanning calorimetry (DSC), electrochemical-impedance spectroscopy (EIS) and solid-state nuclear magnetic resonance (NMR) diffusion measurements. The structure and electrochemical properties of extruded electrolytes were compared with cast films. It was found that TPU, having in its structure, both soft segments from polyol regions and hard segments from isocyanate not only improves the mechanical properties of neat PEO-based polymer electrolyte, but also forms complexes with lithium salt and serves as a conducting medium. Bulk conductivity vs. temperature dependencies obey Arrhenius behavior. The highest conductivity values varying from 0.3 to 1mS/cm over a temperature range from RT to 90ºC were achieved for the extruded 1:15 (Li:EO) solid polymer electrolyte. The NMR tests show that lithium self-diffusion coefficients in extruded PE with alumina filler are close to that in cast PE, but the anion diffusion coefficients (accessible through 19F NMR) are lower in extruded filaments, indicating a correspondingly higher Li+ transference number induced by the extrusion. Lithium cells with extruded LFP cathode and solid extruded polymer electrolyte demonstrated 40 reversible cycles with close to 96% coulombic efficiency. The electrochemical performance of half-cells composed of extruded LFP-based cathode and extruded TPU-MWCNT-based current collector will be presented.

Water behavior at PEMFC triple phase boundary: Exploring ionomer and catalytic layer effects via molecular dynamic simulations and NMR experiments

Polymer electrolyte membrane fuel cells (PEMFCs) offer a clean and efficient energy generation technology. However, optimizing their performance in terms of water transport through the electrolyte membrane remains a challenge. In this study, we employ molecular dynamics simulation and nuclear magnetic resonance (NMR) experiments to investigate the influence of carbon materials and membrane thickness on water diffusion within the triple phase boundary of a PEMFC. Our theoretical investigation highlights the significant impact of Nafion content on water morphology within the system. The structural analysis reveals the intricate interplay between material properties and water behavior in confined environments. The formation of water channels facilitated by the ionomer enhances water mobility, while excessive ionomer content leads to reduced diffusion coefficients. Experimental measurements using NMR diffusion validate the correlation between our simulation results and real-world observations. Furthermore, our Molecular Dynamic (MD) and NMR studies identify the optimal performance range for ionomer content, with systems containing 12 to 24 oligomers (20–30 % w/w) exhibiting superior water diffusion within Vulcan Carbon (VC) structures. By shedding light on water transport phenomena in PEMFCs, our findings contribute to a better understanding of fuel cell performance and provide valuable insights for the design and optimization of fuel cell systems.

Limits of alkanes confined in mesoporous silica as a probe for geometrical tortuosity. An NMR relaxation study

Diffusion Nuclear Magnetic Resonance experiments offer a means to determine the geometrical tortuosity of a porous matrix, assuming that the interaction between the confined fluid and the confining matrix is negligible. In this, alkanes play a crucial role as molecular probes for polar mesoporous systems, with silica being particularly relevant due to its wide range of technological applications. Despite their inherent hydrophobicity, NMR measurements reveal that alkane/silica interactions become significant when the pore diameter approaches the size of the molecules. This fact is clearly demonstrated through the examination of the longitudinal (T1) and transverse (T2) relaxation times of linear and cyclic alkanes confined within silica mesopores of mean pore sizes: 3, 6, and 15 nm. Noticeably, the interactions are practically negligible in 6 and 15 nm pores, but they become relevant in the smallest ones. T1-T2 correlation maps evidence that relaxation times are influenced by molecular length, shape, and pore diameter. These empirical results not only corroborate previous theoretical findings but also highlight the ratio T1/T2 as a valuable, rapid, and cost-effective experimental tool for assessing the feasibility of a given solvent as a molecular probe for determining geometrical tortuosity.

Transport Mechanism in Nafion Revealed by Detailed Comparison of 1H and 17O Nuclear Magnetic Resonance Diffusion Coefficients.

We use 1H and 17O NMR static field gradient diffusometry to measure self-diffusion coefficients of protons (DH) and oxygens (DO) in Nafion 212 with various hydration levels (λ = 4-18). For all samples and both nuclei, we obtain activation energies (Ea) of ≈0.19 eV. Analyzing the hydration-level dependence of DH and DO, we find DO/DH ≈ 1 at λ ≈ 18, resembling the situation in bulk water, while oxygen diffusion becomes faster than proton diffusion when the water content is decreased, leading to DO/DH ≈ 1.2 at λ ≈ 4. A comparison with literature data for acidic bulk solutions implies that faster oxygen than proton diffusion results from the existence of the polymer framework. To rationalize the observed ratios DO/DH ≥ 1, we consider a bimodal dynamical model in which the interactions of H+(H2O)m ions with neighboring SO3- groups lead to slower water dynamics in the vicinity of the polymer framework than in the center of the water nanochannels.

Elucidation of lipid nanoparticle surface structure in mRNA vaccines

Lipid nanoparticles (LNPs) have been used as a carrier for messenger RNA (mRNA) vaccines. Surface properties of LNPs are important to the stability and function of mRNA vaccines. Polyethylene-glycol (PEG) is a functional lipid at the surface of LNPs that improves colloidal stability, increases circulation time, and impacts cellular uptake. In this study, we explore in-depth lipid composition at the surface of mRNA-LNPs using high-field nuclear magnetic resonance (NMR) spectroscopy. Our results provide a unique surface lipid profile of intact LNPs identifying PEG chains and partial ionizable lipids are present with quantification capability. The surface PEG density is determined to reveal the brush-like conformation on the surface of mRNA-LNPs. Furthermore, we implement a diffusion NMR strategy for routine testing of formulated drug products during drug development. Comparative NMR analysis of different vaccine preparations and stability samples provides a global view of the mRNA-LNP surface structure for enhanced product knowledge.

Evaluation of nuclear magnetic resonance spectroscopy for characterisation and quantitation of water-soluble polymers in river water

Water-soluble polymers (WSPs) are commonly used in industrial, commercial, agricultural and pharmaceutical products and their molecular weights and concentrations vary considerably. Methods commonly used in the analysis of WSPs are often for pure products or formulations with only a few other high MW constituents. These methods, like size exclusion chromatography (SEC) or Gel Permeation Chromatography coupled with Mass Spectrometry (MS) can be frustrated by the impact of the necessary separation steps prior to identification and the limitations of MS when identifying and quantifying polymers. To that end, the employment of a Nuclear Magnetic Resonance (NMR) method to identify, characterize and quantify WSPs in the real-world is reported for the first time. Samples were taken from fourteen UK inland river sites, concentrated via air-drying, freeze-drying or vacuum-drying and analyzed using 1D 1H NMR and 2D 1H Diffusion Ordered Spectroscopy (DOSY) NMR analysis. Seven of the river sites showed the presence of polyethylene glycol (PEG) with a range of molecular weights, evidencing the application of these techniques in analysis of WSPs. Soil percolation models evidenced the proof of principle that these techniques can also be used for the detection of polyacrylamide (PAM) and polyacrylic acid (PAA). This work should better enable the evaluation of the biological impact of WSPs on aquatic organisms in future studies.

Structure and Ionic Conductivity of Li-Disordered Bismuth o-Thiophosphate Li60-3xBi16+x(PS4)36.

The structure of the first lithium-containing bismuth ortho (o)-thiophosphate was determined using a combination of powder X-ray, neutron, and electron diffraction. Li60-3xBi16+x(PS4)36 with x in the range of 4.1-6.5 possesses a complex monoclinic structure [space group C2/c (No. 15)] and a large unit cell with the lattice parameters a = 15.4866 Å, b = 10.3232 Å, c = 33.8046 Å, and β = 85.395° for Li44.4Bi21.2(PS4)36, in agreement with the structure as observed by X-ray and neutron pair distribution function analysis. The disordered distribution of lithium ions within the interstices of the dense host structure and the Li ion dynamics and diffusion pathways have been investigated by solid-state nuclear magnetic resonance (NMR) spectroscopy, pulsed field gradient NMR diffusion measurements, and bond valence sum calculations. The total lithium ion conductivities range from 2.6 × 10-7 to 2.8 × 10-6 S cm-1 at 20 °C with activation energies between 0.29 and 0.32 eV, depending on the bismuth content. Despite the highly disordered nature of lithium ions in Li60-3xBi16+x(PS4)36, the underlying dense host framework appears to limit the dimensionality of the lithium diffusion pathways and emphasizes once more the necessity of a close inspection of the structure-property relationships in solid electrolytes.

Drude Polarizable Lipid Force Field with Explicit Treatment of Long-Range Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids.

Accurate empirical force fields of lipid molecules are a critical component of molecular dynamics simulation studies aimed at investigating properties of monolayers, bilayers, micelles, vesicles, and liposomes, as well as heterogeneous systems, such as protein-membrane complexes, bacterial cell walls, and more. While the majority of lipid force field-based simulations have been performed using pairwise-additive nonpolarizable models, advances have been made in the development of the polarizable force field based on the classical Drude oscillator model. In the present study, we undertake further optimization of the Drude lipid force field, termed Drude2023, including improved treatment of the phosphate and glycerol linker region of PC and PE headgroups, additional optimization of the alkene group in monounsaturated lipids, and inclusion of long-range Lennard-Jones interactions using the particle-mesh Ewald method. Initial optimization targeted quantum mechanical (QM) data on small model compounds representative of the linker region. Subsequent optimization targeted QM data on larger model compounds, experimental data, and dihedral potentials of mean force from the CHARMM36 additive lipid force field using a parameter reweighting protocol. The use of both experimental and QM target data during the reweighting protocol is shown to produce physically reasonable parameters that reproduce a collection of experimental observables. Target data for optimization included surface area/lipid for DPPC, DSPC, DMPC, and DLPC bilayers and nuclear magnetic resonance (NMR) order parameters for DPPC bilayers. Validation data include prediction of membrane thickness, scattering form factors, electrostatic potential profiles, compressibility moduli, surface area per lipid, water permeability, NMR T1 relaxation times, diffusion constants, and monolayer surface tensions for a variety of saturated and unsaturated lipid mono- and bilayers. Overall, the agreement with experimental data is quite good, though the results are less satisfactory for the NMR T1 relaxation times for carbons near the ester groups. Notable improvements compared to the additive C36 force field were obtained for membrane dipole potentials, lipid diffusion coefficients, and water permeability with the exception of monounsaturated lipid bilayers. It is anticipated that the optimized polarizable Drude2023 force field will help generate more accurate molecular simulations of pure bilayers and heterogeneous systems containing membranes, advancing our understanding of the role of electronic polarization in these systems.

Numerical simulation study on the effect of temperature on the restricted diffusion in porous media

It is of great significance to study how temperature affects the restricted diffusion in pores for an accurate evaluation of reservoir physical properties by using nuclear magnetic resonance (NMR) diffusion-transverse relaxation (D-T2) spectrum under reservoir temperature conditions. In this paper, we simulate the restricted diffusion and two-dimensional (2D) NMR D-T2 spectra of water molecules at different temperatures using random-walk method. The one-dimensional (1D) restricted diffusion simulation results show that the diffusion coefficient in the pore at room temperature decays with the diffusion time and eventually reaches a plateau. Under the condition of long-time diffusion, the ratio of restricted diffusion coefficient to bulk diffusion coefficient at different temperatures tends to be the same constant. With the increase in temperature, the simulated D-T2 spectra also gradually move upward. The simulated D-T2 spectra at all temperatures are consistent with the Padé interpolation equation. In addition, the results calculated by Padé interpolation equation demonstrate that the degree of temperature influence on the D-T2 spectrum of rock is quantitatively related to the pore radius, porosity and cementation index.

NMR relaxation and diffusion studies to probe the motional dynamics of risperidone within PLGA microsphere

The present study aims to investigate the motional dynamics of risperidone within polylactic co-glycolic acid (PLGA) microsphere by employing solution state 1H and 19F nuclear magnetic resonance (NMR) measurements. Risperidone, a second-generation fluorinated antipsychotic drug used for the treatment of schizophrenia is commercially marketed as PLGA microsphere formulation resulting in prolonged release of the drug in solution. Although the current trend in the pharmaceutical market is to develop drug formulation with long-acting release (LAR) products, complete physicochemical characterization of such formulations are scarce. Especially the effects of microsphere encapsulation on the motional properties and diffusion behavior of the drugs are not discussed adequately in any of the earlier reports. We therefore, have employed NMR relaxation and diffusion measurements to decipher the interaction of PLGA cavity water with risperidone. A detailed analysis of NMR relaxation rates confirmed the event of encapsulation and the presence of local motion in the non-fluorinated end of risperidone. Further, the relaxation data indicated a significant alteration in 19F chemical shift anisotropy (CSA) and CSA/dipole-dipole (DD) cross-correlated relaxation mechanism and decreased effect of solvent relaxation pointing out reduced water concentration within the microsphere cavity. 1H and 19F diffusion coefficients of risperidone led to the information about hydrodynamic radius of risperidone in free and encapsulated states. Measurement of hydrodynamic radius supported the presence of limited water in PLGA cavity allowing higher translational mobility of risperidone after the encapsulation.

Determination of soil pore size distribution and water retention curve by internal magnetic field modulation at low field 1H NMR

The determination of the soil pore size distribution, water retention curve, and derived parameters that control important processes in soils, such as water supply for plants; infiltration; water and solute movement in soils; erosion; plant nutrients and contaminants transport, etc, are challenging and the available methods are expensive, time-consuming and prone to bias and errors. The use of 1H Nuclear Magnetic Resonance (NMR) relaxometry to characterise the soil porosity and hydraulic properties through spin-lattice and spin-spin relaxometry results in an ill-posed problem with two correlated unknown quantities: the pore length scales, and surface relaxivity. To overcome this limitation of NMR relaxometry, we propose the use of a method that directly accesses the NMR diffusion modes governed only by the pore size, and therefore, independent of the unknown surface relaxivity. The manuscript describes an unprecedent application in Soil Science of the Decay due to Diffusion in Internal Field (DDIF) method to successfully determine the pore size distribution of undisturbed soil samples, as well as to estimate the water retention curves from the pore size distribution.

Monitoring cheese ripening by single-sided nuclear magnetic resonance

The noninvasive, longitudinal study of products and food processing is of interest for the dairy industry. Here, we demonstrated that single-sided nuclear magnetic resonance (NMR) can be used for noninvasive monitoring of the cheese ripening process. The maturation of soft-ripened Camembert-like molded cheese samples was monitored for 20 d measuring 1-dimensional and 2-dimensional NMR relaxation and diffusion data at various depths, ranging from the hard surface layer to the soft center. Gelation and gel shrinkage were observed throughout ripening, and a complete loss of free water signal was observed at the cheese rind. Transversal (T2) relaxation distributions include 3 components that evolve with ripening time and position, corresponding to water inside the casein gel network, water trapped in casein, and fat. Two-dimensional T1-T2 relaxation experiments provided enhanced resolution of the 3 components, allowing quantification of the relative proportions of each phase. Furthermore, diffusion (D)-T2 relaxation correlation experiments revealed the bimodal size distribution of fat globules. The study demonstrated that single-sided NMR can provide spatially resolved signal intensity, relaxation, and diffusion parameters that reflect structural changes during the ripening process and can be exploited to understand and monitor the ripening of cheeses.

Enhanced piroctone olamine retention from shampoo for superior anti-dandruff efficacy.

Dandruff is a pervasive chronic condition which negatively impacts quality of life. Effective treatment requires efficient delivery of scalp benefit agents that control commensal scalp Malassezia levels. Delivery of benefit agents from shampoos requires balancing many technical parameters to achieve the desired outcome without sacrificing secondary parameters, such as cosmetic attributes. To develop formulation technologies that increase the shampoo delivery efficiency of the scalp benefit agent piroctone olamine (PO). Increased delivery should result in increased anti-dandruff efficacy. Micellar Stability and Association parameters were quantified via dynamic surface tension and nuclear magnetic resonance (NMR) diffusion parameters, respectively. PO delivery has been assessed in vivo both on the scalp surface and follicular infindibula using extraction procedures and analytical analysis. Clinical anti-dandruff efficacy was assessed for an advanced delivery technology prototype in comparison to standard delivery technology. Shampoo prototypes have been developed that increase the delivery efficiency of PO. Both surfactant and polymer coacervate-based approaches have been developed. Decreased micellar stability results in weaker association between PO and micelles, resulting in more efficient PO retention on the scalp surface and delivery to the infundibula. Increased charge density of cationic polymers optimizes coacervation enabling improved PO delivery as well. Increased PO delivery has been shown clinically to result in higher anti-dandruff efficacy as measured by both visible flakes and underlying biomarkers. Increased efficiency PO delivery shampoos have been developed by optimization of both surfactant and coacervate parameters. The increased deposition efficiency results in significantly more products with significantly greater anti-dandruff efficacy.